Five years follow‐up of mandibular 2‐implant overdentures on locator or ball abutments: Implant results, patient‐related outcome, and prosthetic aftercare
Bibliographic record
Abstract
BACKGROUND: It is uncertain, which is the optimal attachment for a mandibular 2-implant overdenture (2IOD). PURPOSE: To assess 5 years clinical implant outcome, prosthetic maintenance, cost, and PROMs of two cohorts receiving 2IOD on ball or stud abutments in a comparative study. MATERIALS AND METHODS: Ninety edentulous individuals were treated with balls (n = 34) or locator (n = 56). Implant survival, bone-to-implant level, prosthetic outcome, technical maintenance, and OHIP-14 were assessed. Statistics to compare between baseline and 1/5 years and between groups were t-test or Mann-Whitney (P < .05); chi-square was adopted to analyze plaque and technical maintenance or interventions between groups. RESULTS: Five years implant survival was 98.7%, irrespective of attachment. Overall mean bone loss was 1.1 mm, probing pocket depth 1.92 mm, bleeding score 0.60, plaque score 1. Plaque accumulated more on locators (P = .023). OHIP-14 declined from 18.1 to 2.7 irrespective of attachment. Retention for balls was better (P < .005), locators required more maintenance (P < .001), caused by retention-adjustment (P < .001) or ulcers/pain (P = .014). Five years maintenance-cost was 11% of initial cost, irrespective of attachment. CONCLUSIONS: Balls and locators yield stable 5-years implant outcome and improved Oral Health Related Quality of Life (OHRQoL). Locators required more maintenance and resulted in a lower retention. Maintenance costs are minimal but may affect OHRQoL at least for stud abutments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".